Patient Specific Congestive Heart Failure Detection From Raw ECG signal

In this study; in order to diagnose congestive heart failure (CHF) patients, non-linear second-order difference plot (SODP) obtained from raw 256 Hz sampled frequency and windowed record with different time of ECG records are used. All of the data rows are labelled with their belongings to classify much more realistically. SODPs are divided into different radius of quadrant regions and numbers of the points fall in the quadrants are computed in order to extract feature vectors. Fisher's linear discriminant, Naive Bayes, Radial basis function, and artificial neural network are used as classifier. The results are considered in two step validation methods as general k-fold cross-validation and patient based cross-validation. As a result, it is shown that using neural network classifier with features obtained from SODP, the constructed system could distinguish normal and CHF patients with 100% accuracy rate. KeywordsComment: Congestive heart failure, ECG, Second-Order Difference Plot, classification, patient based cross-validatio

IMPROVING THE STUDENT’S OPINION ABOUT THE NATURE OF SCIENCE WITH THE PROCESS-BASED ACTIVITIES BY THE TEACHERS WHO GET DISTANCE EDUCATION ABOUT THE NATURE OF SCIENCE

The purpose of this research is to identify the effect of the activities on student’s opinion about the science nature which is prepared with the explicit reflective teaching approach and integrated with 9th grade biology lesson syllabus by the teachers who gets distance education about teaching the nature of science. For that purpose, in this research, quasi experimental design with pretest and posttest control group has been used. For that purpose, in this research, quasi experimental design with pretest and posttest control group has been used. 2 teachers and 114 students in an Anatolian High School in Meram/Konya have participated in this research in the whole 2014-2015 academic year. In this project, BDHGA Form C (a survey on the ideas about nature of the science), and YYG (semi-structured interview) and Rubic are used as data collecting tools. The qualitative data of the research has been analyzed with content analysis, descriptive analysis and document review. The quantitative data has been analyzed with the SPSS 17 software using ANOVA and T-test for related samples. According to the both quantitative and qualitative data obtained from the research, the experiment class, in which the teacher educated in distant about nature of science and has taught the topic in process based way to the students, is observed to be more developed in this topic than the other class. Also it is seen that only being educated about science nature of the teachers is not adequate. However, the usage of the explicit reflective activities integrated into syllabus has contributed to the perception of the students about the nature of science topic

An unsupervised learning algorithm: application to the discrimination of seismic events and quarry blasts in the vicinity of Istanbul

The results of the application of an unsupervised learning (neural network) approach comprising a Self Organizing Map (SOM), to distinguish micro-earthquakes from quarry blasts in the vicinity of Istanbul, Turkey, are presented and discussed. The SOM is constructed as a neural classifier and complementary reliability estimator to distinguish seismic events, and was employed for varying map sizes. Input parameters consisting of frequency and time domain data (complexity, spectral ratio, S/P wave amplitude peak ratio and origin time of events) extracted from the vertical components of digital seismograms were estimated as discriminants for 179 (1.8 < <i>M</i><sub>d</sub> < 3.0) local events. The results show that complexity and amplitude peak ratio parameters of the observed velocity seismogram may suffice for a reliable discrimination, while origin time and spectral ratio were found to be fuzzy and misleading classifiers for this problem. The SOM discussed here achieved a discrimination reliability that could be employed routinely in observatory practice; however, about 6% of all events were classified as ambiguous cases. This approach was developed independently for this particular classification, but it could be applied to different earthquake regions

Wind Turbine Conical Tubular Tower Optimization By Using Genetic Algorithm

Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2008Thesis (M.Sc.) -- İstanbul Technical University, Institute of Science and Technology, 2008Yapılan bu tez çalışmasında yatay eksenli 1.5 MW gücünde rüzgar türbinine ait çelik konik kulenin yükseklği boyunca kalınlık optimizasyonu, genetik algoritma yöntemiyle yapılmıştır. Optimizasyon problemi Matlab 7.0 programıyla modellenmiştir. Optimizasyon probleminde çelik kulenin yüksekliği ve tabandan en üst noktaya kadar olan koniklik çapı değişimi sabit kabul edilmiştir. Çelik kulenin yüksekliği tabanda 4.3 m, en üst noktada ise 2.56 m’dir. Kulenin toplam yükseklği ise 52 m dir. Kulenin bulunduğu lokasyon Balıkesir-Bandırma olarak kabul edilmiştir. Kuleye etki eden yükler , ASCE-7 , IEC 61400-1 ,Eurocode 1 , Eurocode 3 ve AISC-89 gibi uluslararası standartlar baz alınarak hesaplanmış olup kulenin mukavemet açısından burkulma kuvveti , eğilme momenti ve birinci doğal frekansı analiz edilmiştir. Kuleye etki eden yükler sırasıyla rüzgarın kule üzerindeki direkt etkisi , rotorun dönmesinden kaynaklanan aerodinamik kuvvetler (WindPACT) , deprem yükü ve rotorun dönmesinden kaynaklanan kule üzerindeki yorulma etkisi optimizasyon problemini oluşturan parametrelerin başında gelmektedir. Çaprazlama, kopyalama ve mutasyon operatörleri genel olarak genetik algoritmanın çekirdek yapısını oluşturmaktadır. Algoritma yapısı içinde bulunan populasyondaki her birey kromozu temsil eder. Kromozomlar ise genlerden oluşur. Bu kapsamda populasyon içindeki kromozomlar 52 m lik kulenin her bir metresindeki kalınlığı temsil etmektedir. Problem çözümünde daha önceden belirlenen kısıt alanı içinde bulunan değerlerin en uygun olanları amaç fonksiyonun çözüm kümesini oluşturmuştur.In this study, the thickness of steel conical tower pertaining to horizontal axis 1.5 MW wind turbine was optimized and minimized along the height of tower in lieu of the genetic algorithm method. The optimization problem was solved by Matlab 7.0. In the optimization problem, the height of tower was considered as a constant value. In addition, the change of tower diameter remains steadily from base to top along the tower height. The base diameter and top diameter are 4.3 m and 2.56 m respectively. The total height of tower considered to be located in Balıkesir-Bandırma is 52 m. Buckling strength , bending moment and first mode of natural frequency subjected to the tower were calculated based on ASCE-7 , IEC 61400-1, Eurocode 1, Eurocode 3 and AISC-89 international standards. The loads on the tower representing objective function in the optimization problem are direct wind load, wind turbine load (WindPACT), earthquake load and fatigue load. Also the main parameter in objective function is the weight of the tower. Genetic algorithm structure comprises of reproduction, crossover and mutation operators. In the structure of population of genetic algorithm, each individual represents chromosome which is composed of genes. In this way, the thickness of each 1 m section of tower corresponds to chromosomes. The best ones of values previously determined in allowable constraint area was formed the solution set of objective function.Yüksek LisansM.Sc

Morphometric risk factors effects on anterior cruciate ligament injury

Objectives: This study aims to compare the morphometric differences between patients with and without an anterior cruciate ligament (ACL) injury and to investigate the anatomical risk factors associated with ACL injury. Patients and methods: Between February 2020 and February 2022, a total of 100 patients (57 males, 43 females; mean age: 36.2 +/- 6.8 years; range, 18 to 45 years) who were operated for isolated non-contact ACL tear as the patient group and a total of 100 healthy individuals (58 males, 42 females; mean age: 35.0 +/- 6.9 years; range, 18 to 45 years) without an ACL tear as the control group were included. Magnetic resonance imaging scans of the knee joint were included in the study. Morphological variables of the ACL, distal femur, proximal tibia, and menisci were measured. Results: The mean ACL inclination angle and medial meniscus bone angle were 37.7 +/- 3.8 and 20.2 +/- 2.9 in the patient group and 48.1 +/- 3.3 and 25.0 +/- 2.9 in the control group. According to the results of multivariate analysis, those with small ACL inclination angle and medial meniscus bone angle were more likely to have ACL tear (odds ratio: 0.128, intraclass correlation coefficient: 0.038-0.430, p= 0.001). Conclusion: Small ACL inclination angle and medial meniscus bone angle can be a risk factor for ACL tear

Investigation of the blastocystis hominis frequency in patients with irritable bowel syndrome

AimIn this study, it was aimed to investigate the relationship between Blastocystis hominis infection and inflammatory bowel syndrome (IBS). Methods: In this study, the frequency of B. hominis in the stool samples of 52 patients applied to Microbiology laboratory and pre-diagnosed with irritable bowel syndrome in January 2013-June 2013 was investigated, retrospectively. Microscopic investigations were evaluated after macroscopic examination. For this purpose, the stool samples of the diarrheal cases were investigated by trichrome staining after they were prepared by native-lugol and formol ethyl acetate concentration method. The results were compared with the examination of 2160 stool samples sent to our laboratory during the same period. Results: Stool samples of 52 patients pre-diagnosed with IBS were accepted to our laboratory in January 2013-June 2013. 13 of the patients were found as B. hominis positive. Weight loss and anorexia was identified only in one patient while abdominal pain, diarrhea and gas complaints were identified in all of the IBH and B. hominis positive patients. During the same period, parasites were detected in 96 (4.4%) of 2160 stool samples sent to our laboratory and the most common was B. hominis 48 (2.2%). 452 of these patients applied with diarrhea symptoms and B. hominis was detected in 36 samples (7.96%). Conclusion: The limited studies investigating the presence of B. hominis in patients with irritable bowel syndrome are far from illuminating the role of this agent in disease pathogenesis. We believe that further investigations should be performed. In this study, 25% of the patients were found as positive. J Clin Exp Invest 2014; 5 (2): 242-24

Comparison of diferent lactation curve models of Anatolian Bufaloes

Bu araştırmada, farklı işletme koşullarında 2011-2013 yılları arasında yetiştirilen Anadolu mandalarına ait kontrol günü süt verim kayıtları kullanılarak sekiz farklı laktasyon eğrisi modeli karşılaştırılmıştır. Bu amaçla, laktasyon eğrisinin tanımlanmasında Wood, Cobby ve Le Du, Üssel, Parabolik Üssel, Kuadratik, Ters Polinomiyal, Logaritmik Kuadratik, Logaritmik Linear modelleri kullanılmıştır. Laktasyon eğrisini en iyi tanımlayan modeli belirlemek için belirtme (R2) ve kalıntı standart sapma (KSS) katsayıları kriter olarak kullanılmıştır. En yüksek R2 ve en düşük KSS değerlerini veren Logaritmik Kuadratik ve Kuadratik modellerin en iyi uyumu gösteren modeller olduğu belirlenmiştir. Sonuç olarak, Logaritmik Kuadratik veya Kuadratik modeller ile tahmin edilen parametrelerin ıslah çalışmalarında kullanılması, bu yönde yapılacak araştırmalara önemli katkı sağlayacaktır.In this study, eight diferent lactation curve models were compared by using test day milk yield records belonging Anatolian Bufaloes raised in diferent Farm conditions between 2011 and 2013. To identify the best lactation curve models of Wood, Cobby and Le Du, Logaritmic Quadratic, Exponential, Parabolic exponential, Quadratic, Inverse Polynomial and Logaritmic Linear mathematical functions were used. The coefficient of determination (R2) and residual standard deviation (RSD) statistics were used for determination of best fitted model in lactation curve. Logaritmic Quadratic and Quadratic functions are the best goodness of fit model as having the highest R2 and lowest RSD coefficients. As a result, the parameters are estimated by logarithmic quadratic or quadratic models, for use in breeding programs will make an important contribution to research in this field

Intragastric Migration of Gastric Band Diagnosed During Surgery: A Case Report and Literature

Intragastric band migration (IGBM) is one of the major complications of gastric banding. In this report, we aimed to present a case of IGBM, which was diagnosed intraoperatively, and to review the relevant literature. A 59-year-old male patient was admitted to our outpatient clinic due to epigastric pain persisting for the past three months. The patient had a history of gastric banding surgery owing to obesity with open surgery nine years ago. Postoperative follow-up was not done properly and the patient had started to gain weight in the third postoperative year. Incisional hernia was found in physical examination and operation for gastric band removal and hernia repair was planned. During surgery, the band could not be found around the stomach, therefore, gastroscopy was performed and it was found that the majority of the band was placed in the stomach. The patient was intraoperatively diagnosed with IGBM and the band was removed through gastrotomy, and hernia repair was performed. The patient was discharged at postoperative 6th day without any complication. Although IGBM is rarely seen, it should be considered as a long-term complication in cases with dysfunctional gastric band and in patients who started to gain weight after operation. Treatment is the removal of the band review

Role of tumor location on high-grade serous ovarian cancer prognosis

Objectives: Ovarian cancer is associated with the highest mortality of gynecologic cancers. Epidemiological and genetic factors of ovarian cancer development are clearly defined but prognostic factors have not been adequately identified. Right and left ovarian cancers seem to act different behaviors at high-grade serous ovarian cancer (HGSOC) prognosis. The aim of this study is to explain this prognostic role of its sidedness. The aim of this study is to explain this prognostic role of its sidedness. Material and methods: We reviewed 160 consecutive patients with Figo stage 1-3 HGSOCs and undergone surgery at two high-volume hospitals. Prognostic effects of primary tumor location onset were evaluated in terms of 5-year disease free survival and overall survival rate. Results: One hundred-sixty patients with ovarian cancer records were analyzed using the Kaplan-Meier method, that demonstrated a significant difference in the 5-year disease-free survival rates between right and left-sided cancers for all stages (44.6% vs 78.5%, p < 0.001). Also, there was significant difference in the 5-year overall survival rates between the two groups (71.1% vs 91.9%, p = 0.020). Conclusions: Tumor location within the HGSOC seems to be a compelling prognostic factor ovarian cancer. Further prospective studies are needed in order to support our hypothesis

Epileptic state detection : Pre-ictal, inter-ictal, ictal

Epileptic seizure detection and prediction from electroencephalography (EEG) is a vital area of research. In this study, SecondOrder Difference Plot (SODP) is used to extract features based on consecutive difference of time domain values from three states of EEG (pre-ictal, ictal and inter-ictal), and Multi-Layer Neural Network classifier is used to classify these three classes. The proposed technique is tested on a publicly available EEG database and classified with Naive Bayes and k-nearest neighbor classifiers. As a result, it is shown that overall accuracy of 98.70% can be achieved by using the proposed system with Neural Network classifier.Epileptic seizure detection and prediction from electroencephalography (EEG) is a vital area of research. In this study, SecondOrder Difference Plot (SODP) is used to extract features based on consecutive difference of time domain values from three states of EEG (pre-ictal, ictal and inter-ictal), and Multi-Layer Neural Network classifier is used to classify these three classes. The proposed technique is tested on a publicly available EEG database and classified with Naive Bayes and k-nearest neighbor classifiers. As a result, it is shown that overall accuracy of 98.70% can be achieved by using the proposed system with Neural Network classifier